Broad rationale:

• Nutrient enrichment is recognized as a major threat to biodiversity worldwide

• Question of scale - constant problem in ecology.

• Much of our understanding of how nitrogen enrichment impacts plant diversity comes from small-scale experiments - responses observed in a 1m2 plot or smaller

• Extrapolating from the results of these small-scale experiments to broader patterns comes with some caveats

  • Many ecological phenomena exhibit scale-dependence, particularly with respect to spatial scale of sampling

    • Examples: Spatial scaling and invasion effects (Powell et al. 2013)
    • Lan et al. (2015) J. Ecology
    • Chase et al. (2018) BioRxiv

• Because many experiments evaluate effects at a single spatial scale, you’re likely to miss nuanced interpretation that can produce meaningful insights into how different environmental stressors impact plant diversity.

Nutrient enrichment

• Nutrient enrichment (particularly nitrogen) is a highly pervasive environmental stressor

  • Worldwide patterns of N deposition, nutrient runoff, etc.

• Fertilization increases plant growth and intensity of light competition that favors large, fast growing species

• Notion of niche collapse - addition of a limiting nutrient reduces relevant variation in its contribution to species fitness

  • Therefore, addition of multiple limiting nutrients can have greater effects than saturation of a single resource

  • When resources are spatially heterogeneous, nutrient addition can act as a homogenizing force

Introduce California annual grasslands

• High plant diversity, despite invasive history

• High spatial heterogeneity of vegetation and soil resources

Introduction to accumulation curves

• To quantify spatial scale-dependence, classic approaches utilze species-accumulation curves which relate observed diversity to sampling effort.

• We can use these curves to determine how effects vary with scale, and identify whether effects increase or decrease with spatial scale, as well as inflection points where interpetation flips.

• However, when species accumulation curves are composed of individual sampling subunits, we can also vary the way in which we accumulate diversity (spatially or randomly) - detecting the influence of spatial processes on the shape of this relationship, such as spatial aggregation (clustering of individuals)

Accumulation curve figure:

• Show two communities - one with a greater number of species at the gamma scale and lower species richness per sample unit + aggregation, one with a smaller number of species at the gamma scale and lower species richness per sample unit + no aggregation.

• Demonstrate the steps to my analysis (borrowing elements of the analysis framework of McGlinn et al. (2018)):

  • Alpha, gamma, and beta diversity - the endpoints of this relationship

  • Spatial accumulation order + its resulting curve

  • Random accumulation order + its resulting curve

  • Mean difference in these curves (aggregation effect in each community)

  • Relative contribution of aggregation effect to the shape of this scaling relationship (net change)

• Can also reference difference in weighting effective numbers of species metrics

Why distinguishing between these mechanisms matters

Questions

• Do nutrient enrichment effects vary with spatial scale?

• Does use of abundance weighted metrics change our interpretation of effects?

• How does spatial aggregation contribute to the observed differences between curves?

Study design

• Reserves + plot layout

Response variables measured

• Plant biomass change

• Light availability change

• Community composition

Confirming the resource limitation of communities

• Biomass change over time

• Light availability change over time

Light Meter Readings.

Community composition change

• Raw species area curves:

2017 Species Richness Accumulation

2017 Effective Number of Species Accumulation

2018 Species Richness Accumulation

2018 Effective Number of Species Accumulation

Two-scale analysis (endpoints of the curve)

• Difference in alpha/beta/gamma diversity over time (bar plot)

Alpha Change.

Beta Change.

Gamma Change.

Construction of random species area curves (Show together for 2018?)

• Net effect over scales (nonlinear patterns for Q = 0, more linear patterns for Q = 2)

• Change in net effect (greater effect at intermediate scales than otherwise)

Quantifying this aggregation effect

• Average aggregation effect in communities

Species richness aggregation effect

ENSpie aggregation effect